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CDC
2010
IEEE
106views Control Systems» more  CDC 2010»
14 years 11 months ago
Observational learning in an uncertain world
We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal ...
Daron Acemoglu, Munther A. Dahleh, Asuman E. Ozdag...
TIT
2002
125views more  TIT 2002»
15 years 3 months ago
Optimal bi-level quantization of i.i.d. sensor observations for binary hypothesis testing
We consider the problem of binary hypothesis testing using binary decisions from independent and identically distributed (i.i.d). sensors. Identical likelihood-ratio quantizers wit...
Qian Zhang, Pramod K. Varshney, Richard D. Wesel
TSP
2010
14 years 11 months ago
Joint detection and estimation of multiple objects from image observations
The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as ...
Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Sute...
AAAI
2008
15 years 6 months ago
Studies in Solution Sampling
We introduce novel algorithms for generating random solutions from a uniform distribution over the solutions of a boolean satisfiability problem. Our algorithms operate in two pha...
Vibhav Gogate, Rina Dechter
CORR
2007
Springer
112views Education» more  CORR 2007»
15 years 4 months ago
Learning from compressed observations
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...
Maxim Raginsky